Earth System Modelling with Galaxy
The Community Earth System Model (CESM) from the National Center for Atmospheric Research is a fully-coupled, community, global climate model allowing state-of-the-art computer simulations of the Earth’s past, present and future climates. The Norwegian Earth System Model (NorESM) builds on it, with...
| Main Authors: | , |
|---|---|
| Format: | Conference Object |
| Language: | unknown |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://zenodo.org/record/4047827 https://doi.org/10.5281/zenodo.4047827 |
| Summary: | The Community Earth System Model (CESM) from the National Center for Atmospheric Research is a fully-coupled, community, global climate model allowing state-of-the-art computer simulations of the Earth’s past, present and future climates. The Norwegian Earth System Model (NorESM) builds on it, with major changes in the aerosol-cloud chemistry (developed at the Meteorological Institute and University of Oslo), the ocean and its biogeochemistry (originally Miami Isopycnic Coordinate Ocean Model and Hamburg Model of Ocean Carbon Cycle, respectively, modified at the University of Bergen, Nansen Environmental and Remote Sensing Center, and Norwegian Research Center AS). In addition schemes are implemented to compute turbulent atmosphere-ocean fluxes, for atmospheric energy and momentum conservation, etc. Basically CESM/NorESM are composed of separate components to simulate the Earth’s atmosphere, ocean, land, river run-off, land-ice, and sea-ice, plus one central coupler/moderator synchronizing exchanges between them. CESM/NorESM make it possible to conduct fundamental research into the biological, geophysical and chemical processes governing the system and to explore socioeconomic scenarios for instance in Coupled Model Intercomparison Projects (CMIPs). Users of CESM/NorESM (or similar models) do not have the same computational resource needs. On the one side production (to simulate hundreds or thousands of years) demand maximum power (in Petaflops range) which only large national and European High-Performance Computers (HPCs) can deliver. On the other side, for model developments, debugging, testing and validation as well as for teaching purposes what matters most is a flexible framework. For post-processing, analysis and visualization of model data, co-location of the tools (Jupyter notebooks, as an example) and data is paramount to avoid transfers. When it comes to collaborations and reproducible research, sine qua non conditions are the possibility of sharing files and using the same run-time environment. Far ... |
|---|